Reactive oxygen species–associated molecular signature predicts survival in patients with sepsis
Affiliation
Univ Arizona, Dept MedUniv Arizona, Dept Biomed Engn
Issue Date
2016-06
Metadata
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UNIV CHICAGO PRESSCitation
Reactive oxygen species–associated molecular signature predicts survival in patients with sepsis 2016, 6 (2):196 Pulmonary CirculationJournal
Pulmonary CirculationRights
© 2016 by the Pulmonary Vascular Research Institute. All rights reserved.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Sepsis-related multiple organ dysfunction syndrome is a leading cause of death in intensive care units. There is overwhelming evidence that oxidative stress plays a significant role in the pathogenesis of sepsis-associated multiple organ failure; however, reactive oxygen species (ROS)-associated biomarkers and/or diagnostics that define mortality or predict survival in sepsis are lacking. Lung or peripheral blood gene expression analysis has gained increasing recognition as a potential prognostic and/or diagnostic tool. The objective of this study was to identify ROS-associated biomarkers predictive of survival in patients with sepsis. In-silico analyses of expression profiles allowed the identification of a 21-gene ROS-associated molecular signature that predicts survival in sepsis patients. Importantly, this signature performed well in a validation cohort consisting of sepsis patients aggregated from distinct patient populations recruited from different sites. Our signature outperforms randomly generated signatures of the same signature gene size. Our findings further validate the critical role of ROSs in the pathogenesis of sepsis and provide a novel gene signature that predicts survival in sepsis patients. These results also highlight the utility of peripheral blood molecular signatures as biomarkers for predicting mortality risk in patients with sepsis, which could facilitate the development of personalized therapies.Note
On an institutional repository or open access repository after 12 months embargo.ISSN
2045-89322045-8940
DOI
10.1086/685547Version
Final published versionSponsors
Veterans Administration Health System grant [1IK2BX001477]; National Institutes of Health [R01HL91899]Additional Links
http://www.journals.uchicago.edu/doi/10.1086/685547ae974a485f413a2113503eed53cd6c53
10.1086/685547